| 1. |
- Aad, G., et al.
(author)
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- 2015
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In: Journal of High Energy Physics. - : Springer. - 1029-8479 .- 1126-6708. ; :11
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Journal article (peer-reviewed)
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| 2. |
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| 3. |
- Aad, G., et al.
(author)
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- 2015
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In: Physical Review D (Particles, Fields, Gravitation and Cosmology). - 1550-2368 .- 1550-7998. ; 91:11, s. 112011-
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Journal article (peer-reviewed)
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| 4. |
- Li, K., et al.
(author)
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An epidemiologic risk prediction model for ovarian cancer in Europe : the EPIC study
- 2015
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In: British Journal of Cancer. - : Springer Science and Business Media LLC. - 0007-0920 .- 1532-1827. ; 112:7, s. 1257-1265
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Journal article (peer-reviewed)abstract
- Background: Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents. Methods: We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202 206 women in the European Prospective Investigation into Cancer and Nutrition study. Results: Older age at menopause, longer duration of hormone replacement therapy, and higher body mass index were included as increasing ovarian cancer risk, whereas unilateral ovariectomy, longer duration of oral contraceptive use, and higher number of full-term pregnancies were decreasing risk. The discriminatory power (overall concordance index) of this model, as examined with five-fold cross-validation, was 0.64 (95% confidence interval (CI): 0.57, 0.70). The ratio of the expected to observed number of ovarian cancer cases occurring in the first 5 years of follow-up was 0.90 (293 out of 324, 95% CI: 0.81-1.01), in general there was no evidence for miscalibration. Conclusion: Our ovarian cancer risk model containing only epidemiological data showed modest discriminatory power for a Western European population. Future studies should consider adding informative biomarkers to possibly improve the predictive ability of the model.
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| 6. |
- Huesing, Anika, et al.
(author)
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Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status
- 2012
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In: Journal of Medical Genetics. - : BMJ. - 0022-2593 .- 1468-6244. ; 49:9, s. 601-608
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Journal article (peer-reviewed)abstract
- Objective There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Material and methods Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. Results We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Discussion and conclusions Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
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| 7. |
- Fortner, Renee T., et al.
(author)
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Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models : results from the EPIC cohort
- 2017
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In: Journal of Ovarian Research. - : Springer Science and Business Media LLC. - 1757-2215. ; 10
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Journal article (peer-reviewed)abstract
- Background: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening.Methods: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n = 590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression.Results: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p ≤ 0.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend ≤ 0.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p < 0.01). CA15.3 concentrations were higher among heavier women and in former smokers (p ≤ 0.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (≤ 0.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination.Conclusions: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors.
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| 8. |
- Fortner, Renee T., et al.
(author)
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Endometrial cancer risk prediction including serum-based biomarkers : results from the EPIC cohort
- 2017
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In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 140:6, s. 1317-1323
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Journal article (peer-reviewed)abstract
- Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimina-tion. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigat-ed for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selec-tion process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were select-ed into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including eti-ologic markers on independent pathways and genetic markers may further improve discrimination.
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| 9. |
- Hoeft, Birgit, et al.
(author)
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Polymorphisms in fatty acid metabolism-related genes are associated with colorectal cancer risk
- 2010
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In: Carcinogenesis. - : Oxford University Press (OUP). - 0143-3334 .- 1460-2180. ; 31:3, s. 466-472
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Journal article (peer-reviewed)abstract
- Colorectal cancer (CRC) is the third most common malignant tumor and the fourth leading cause of cancer death worldwide. The crucial role of fatty acids for a number of important biological processes suggests a more in-depth analysis of inter-individual differences in fatty acid metabolizing genes as contributing factor to colon carcinogenesis. We examined the association between genetic variability in 43 fatty acid metabolism-related genes and colorectal risk in 1225 CRC cases and 2032 controls participating in the European Prospective Investigation into Cancer and Nutrition study. Three hundred and ninety two single-nucleotide polymorphisms were selected using pairwise tagging with an r(2) cutoff of 0.8 and a minor allele frequency of > 5%. Conditional logistic regression models were used to estimate odds ratios and corresponding 95% confidence intervals. Haplotype analysis was performed using a generalized linear model framework. On the genotype level, hydroxyprostaglandin dehydrogenase 15-(NAD) (HPGD), phospholipase A2 group VI (PLA2G6) and transient receptor potential vanilloid 3 were associated with higher risk for CRC, whereas prostaglandin E receptor 2 (PTGER2) was associated with lower CRC risk. A significant inverse association (P < 0.006) was found for PTGER2 GGG haplotype, whereas HPGD AGGAG and PLA2G3 CT haplotypes were significantly (P < 0.001 and P = 0.003, respectively) associated with higher risk of CRC. Based on these data, we present for the first time the association of HPGD variants with CRC risk. Our results support the key role of prostanoid signaling in colon carcinogenesis and suggest a relevance of genetic variation in fatty acid metabolism-related genes and CRC risk.
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| 10. |
- Poli, Sven, et al.
(author)
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Penumbral Rescue by normobaric O?=?O administration in patients with ischemic stroke and target mismatch proFile (PROOF): Study protocol of a phase IIb trial
- 2024
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In: INTERNATIONAL JOURNAL OF STROKE. - 1747-4930 .- 1747-4949. ; 19:1, s. 120-126
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Journal article (peer-reviewed)abstract
- Rationale: Oxygen is essential for cellular energy metabolism. Neurons are particularly vulnerable to hypoxia. Increasing oxygen supply shortly after stroke onset could preserve the ischemic penumbra until revascularization occurs.Aims: PROOF investigates the use of normobaric oxygen (NBO) therapy within 6 h of symptom onset/notice for brain-protective bridging until endovascular revascularization of acute intracranial anterior-circulation occlusion.Methods and design: Randomized (1:1), standard treatment-controlled, open-label, blinded endpoint, multicenter adaptive phase IIb trial.Study outcomes: Primary outcome is ischemic core growth (mL) from baseline to 24 h (intention-to-treat analysis). Secondary efficacy outcomes include change in NIHSS from baseline to 24 h, mRS at 90 days, cognitive and emotional function, and quality of life. Safety outcomes include mortality, intracranial hemorrhage, and respiratory failure. Exploratory analyses of imaging and blood biomarkers will be conducted.Sample size: Using an adaptive design with interim analysis at 80 patients per arm, up to 456 participants (228 per arm) would be needed for 80% power (one-sided alpha 0.05) to detect a mean reduction of ischemic core growth by 6.68 mL, assuming 21.4 mL standard deviation.Discussion: By enrolling endovascular thrombectomy candidates in an early time window, the trial replicates insights from preclinical studies in which NBO showed beneficial effects, namely early initiation of near 100% inspired oxygen during short temporary ischemia. Primary outcome assessment at 24 h on follow-up imaging reduces variability due to withdrawal of care and early clinical confounders such as delayed extubation and aspiration pneumonia.
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